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Record W2135055349 · doi:10.1093/humrep/deh892

Intra-cervical versus i.v. fentanyl for abortion

2005· article· en· W2135055349 on OpenAlexaff
Ellen Wiebe, Konia Trouton, E. Savoy

Bibliographic record

VenueHuman Reproduction · 2005
Typearticle
Languageen
FieldMedicine
TopicReproductive Health and Contraception
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsFentanylMedicineAbortionAnesthesiaCervical dilationPlaceboRandomized controlled trialLidocainePregnancyMisoprostolGestational ageObstetricsSurgeryGestation

Abstract

fetched live from OpenAlex

BACKGROUND: The majority of abortions are performed using a para-cervical block (without general anaesthesia) and involve a significant amount of pain. If fentanyl was given with the lidocaine in the para-cervical block, it potentially could improve pain control while decreasing side effects and avoiding i.v. access for women having abortions. METHODS: This was a randomized double-blind placebo-controlled trial of two treatment arms: (i) para-cervical block with 100 microg of fentanyl i.v; or (ii) para-cervical block with 100 microg of fentanyl intra-cervically (i.c.) for first trimester abortion. The setting was a free-standing urban abortion clinic. The outcome measures were pain scores and side effects. RESULTS: A total of 104 women received the fentanyl i.v. and 98 received the fentanyl i.c. The two groups were similar with respect to age, gestational age, obstetric history, anxiety and depression. Pain scores (0-10) were 4.7 and 5.7 for dilation (P = 0.01) and 3.8 and 5.6 for suctioning (P < 0.001) in the i.v. and i.c. groups, respectively. Side effects were similar, but more women in the i.v. group received anti-emetics. More women in the i.c. group were dissatisfied with the pain control. CONCLUSION: I.v. fentanyl is more effective than i.c. fentanyl for pain control in abortion.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.729
Threshold uncertainty score0.492

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.054
GPT teacher head0.364
Teacher spread0.310 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations10
Published2005
Admission routes1
Has abstractyes

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